Mingzhu Tang

1.3k total citations · 1 hit paper
41 papers, 1.1k citations indexed

About

Mingzhu Tang is a scholar working on Control and Systems Engineering, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Mingzhu Tang has authored 41 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Control and Systems Engineering, 20 papers in Artificial Intelligence and 14 papers in Electrical and Electronic Engineering. Recurrent topics in Mingzhu Tang's work include Machine Fault Diagnosis Techniques (17 papers), Metaheuristic Optimization Algorithms Research (10 papers) and Energy Load and Power Forecasting (9 papers). Mingzhu Tang is often cited by papers focused on Machine Fault Diagnosis Techniques (17 papers), Metaheuristic Optimization Algorithms Research (10 papers) and Energy Load and Power Forecasting (9 papers). Mingzhu Tang collaborates with scholars based in China, United States and Germany. Mingzhu Tang's co-authors include Wen Long, Jianjun Jiao, Ximing Liang, Ming Xu, Shaohong Cai, Tiebin Wu, Huawei Wu, Qi Zhao, Steven X. Ding and Bin Huang and has published in prestigious journals such as Expert Systems with Applications, Energy and Sensors.

In The Last Decade

Mingzhu Tang

36 papers receiving 1.0k citations

Hit Papers

An exploration-enhanced grey wolf optimizer to solve high... 2017 2026 2020 2023 2017 50 100 150 200

Peers

Mingzhu Tang
Comparison fields: 5 of 83
  • Artificial Intelligence 609
  • Control and Systems Engineering 284
  • Electrical and Electronic Engineering 247
  • Computational Theory and Mathematics 206
  • Renewable Energy, Sustainability and the Environment 179
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Citations per field, relative to Mingzhu Tang
Mingzhu Tang · 1×
Citations per year, relative to Mingzhu Tang
Mingzhu Tang · 1×

Countries citing papers authored by Mingzhu Tang

Since Specialization
Citations

This map shows the geographic impact of Mingzhu Tang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mingzhu Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingzhu Tang more than expected).

Fields of papers citing papers by Mingzhu Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mingzhu Tang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mingzhu Tang. The network helps show where Mingzhu Tang may publish in the future.

Co-authorship network of co-authors of Mingzhu Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Mingzhu Tang. A scholar is included among the top collaborators of Mingzhu Tang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mingzhu Tang. Mingzhu Tang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 0
3 0
4 3
5 29
6 14
7 61
8 8
9 26
10 7
11 17
12 4
13 6
14 3
15 50
16 134
17 18
18 21
19
An exploration-enhanced grey wolf optimizer to solve high-dimensional numerical optimization breakdown →
235
20
Modified support vector data description for fault diagnosis
5

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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